REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO METHODS AND SEGMENTATION ALGORITHMS IN HIDDEN MARKOV MODELS

DOI10.1111/J.1467-842X.2010.00571.XzbMath1337.62146MaRDI QIDQ2810418

Luigi Spezia, Roberta Paroli

Publication date: 1 June 2016

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

zbMATH Keywords

clusteringdigital imagespost-processinglabel-switchingPeano-Hilbert scan

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Image analysis in multivariate analysis (62H35) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (2)

Hierarchical Bayesian Approach to a Multi-Site Hidden Markov Model ⋮ Modelling covariance matrices by the trigonometric separation strategy with application to hidden Markov models

Cites Work

• Calculating posterior distributions and modal estimates in Markov mixture models
• Bayesian estimation of hidden Markov chains: A stochastic implementation
• On Gibbs sampling for state space models
• Hidden Markov Models and Disease Mapping
• Reversible Jump, Birth-and-Death and More General Continuous Time Markov Chain Monte Carlo Samplers
• Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models
• Bayesian Inference in Hidden Markov Models Through the Reversible Jump Markov Chain Monte Carlo Method
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